The Berkman Klein Center for Internet & Society

A Feature or a Bug? | BKC's Jonathan Zittrain in Conversation with Polymarket's Shayne Coplan

Duration: 4:50 857 transcript words EN summary

Video summary

The conversation explores the complex ethical and functional boundaries between insider trading acting as a feature versus a bug within prediction markets like Polymarket. Using vivid examples ranging from a basketball manager delaying game cleanup to tend to an injured player's leg until it impacts betting lines, to a Coinbase executive inadvertently confirming market rumors during an earnings call by listing specific keywords the audience was waiting for, the dialogue illustrates how information asymmetry operates in real-time. These scenarios highlight that markets are not static entities but dynamic systems where participants constantly process new data, such as injury reports or unexpected corporate disclosures, which naturally shifts liquidity and pricing moments before major events like game kick-offs or stock earnings releases. A central argument presented is that the market's reaction to these insights should be viewed as a feature rather than a flaw because it allows for efficient risk management through decentralized intelligence. The speakers explain that professional market makers do not treat these situations as riskless; instead, they develop sophisticated strategies to provide liquidity while pricing in known uncertainties like potential player injuries or unconfirmed rumors about corporate earnings. When information floods the system shortly before an event—whether due to a hamstring pull on the field or a CEO's distracted speech—the resulting price adjustments reflect the collective wisdom of participants who have analyzed decades of game tape and market behavior, effectively anchoring prices to likely outcomes without relying solely on traditional institutional data sources. However, the discussion also acknowledges that these dynamics can lead to unusual occurrences in thin markets where novelty meets high stakes, such as betting on whether specific words will be spoken during a financial call. While instances like tracking bets on what an executive might say before they accidentally confirm them may seem absurd or even risky for individual bettors who wagered heavily based on incomplete information, the broader system remains robust because it is not designed to mimic institutional liquidity markets perfectly but rather to capture unique insights that traditional finance often misses. The consensus suggests that while weird stuff happens with new innovations and gimmicks in this space, the ability of these platforms to incorporate real-time human knowledge into pricing mechanisms represents a significant evolution beyond conventional financial models. Ultimately, the dialogue concludes by reframing insider trading not as an inherent evil but as a nuanced phenomenon where timing and information availability define its nature. In environments like sports betting or crypto earnings calls, the market naturally tightens lines and reduces liquidity when uncertainty peaks before tip-off or kick-off because participants are aware that new information could arrive at any second. This self-regulating mechanism ensures that those who possess superior insights can influence prices appropriately, while market makers adjust their strategies to manage exposure against unknown variables like sudden injuries or off-script executive comments. By leaving the definition of risk and pricing up to the collective action of diverse participants, these prediction markets demonstrate a unique capacity to value information instantly, turning what might appear as insider trading into an integral part of how real-world probabilities are quantified in emerging digital economies.

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But, let me just ask conceptually about is insider trading a feature or a bug, or when it is and when it isn't. The example I gave was kind of getting ahead of things. It was somebody who throws the game in order to win the bet. But, suppose I'm not asking about the basketball player at Michigan. I'm asking about the manager of the team whose job it is to like clean the basketballs after the thing. And well, he comes in and he sees somebody that just tripped on their way into the locker room, and there's bones sticking through their shin. Sorry to be so graphic here. I don't know why I am, but Basically, you know a player is injured, and you stop for a moment polishing the basketball, and you're like, "One moment. I'm going to grab my phone and just take care of something." And I put it all on Michigan losing. Conceptually speaking, is that okay? I mean, you're still taking a huge risk. One guy, you know, getting injured. >> Oh, it was the star person. Okay, I look The the bottom line is like, you know, 3 years ago the exact same thing existed. It's you know, this isn't like a new thing. It's not a So, I The only reason I'm asking, well, it's more reasons than one, but I'm I thought you had at sometime said this might be a feature. Well, yeah. So, look. Anyone who has like partisan sports markets knows that the line gets a lot tighter right before the game. More liquidity comes, more people bet larger size. They'll take larger size. That's because the injury reports were right before. So, the market is not stupid. Uh they understand They They have decades centuries, but decades at least of um game tape, no pun intended, uh of like how the markets move, where there's most risk. And at time for this most risk, let's say in 45 minutes before the game, um or you know, there's a warm up before football, and it's like some guy could pull his hamstring. There's lighter liquidity. People are willing to go and take, you know, give you inventory, supply you liquidity, but at a at a smaller size than right before tip-off or right before kick-off, where there's certainty about who the starting lineups are. So, you know, leave it to the market and leave it to market participants to define and model their own risk uh and and price accordingly. And what you see is you see this in sports markets, you see this in commodities, you see this in stocks for earnings. Like, there are insights about, "Oh, well, you know, they had really strong revenue." Or this and this, there's rumors, etc. That's what's above my pay grade. But, there are insights that go and anchor people to what the likely outcome could be. And they flood the markets shortly before. And my hypo's an example of that kind of insight. Yeah, I mean, look, if there's an injury, like that could totally happen. I think that when you are going and market making and pricing a sports sports game, what are the risks? One of which is that someone knows about an injury that you don't know. It's one of the most prominent ones. Um when you go and provide liquidity and you price markets, that's not because it's riskless. If it were riskless, everyone would do it. It's that you have to go and develop a strategy where you can go provide the service and which is competitive pricing and liquidity, Yeah. while also managing your risk, which in this case is that. There's another kind of fascinating example from uh the Polymarket feed, which I think um uh the feed called devilish. Um it was on a Coinbase earnings call, and where the Coinbase CBO was on the call talking, and there had apparently been some bets about what he would talk about. >> [laughter] >> This happened. I um I was a little distracted because I was tracking the uh prediction market about what Coinbase will say on their next earnings call, and I just want to you know, add here the words Bitcoin, Ethereum, blockchain, staking, and Web3 to make sure we get those in before the end of the call. >> [laughter] >> That's a good one. And I guess is it just sort of like if I were betting my mom's dental work on Ethereum not happening on the call, it's like, well, maybe I should have picked a different bet. I mean, look, I think um you know, no one who's participating in these mention markets, especially something like that, is under the impression this is like a financial, like, you know, institutional liquidity market, right? And these are really thin markets. Um this is the first time something like that's happened, but, you know, just as with any like novelty, new innovation, uh new gimmick, whatever you want to call it, uh you know, you kind of see >> weird stuff. Yeah, yeah.